Name : Zubaidah Bt Abdul Ghani

Student ID : 2009546185

Research Design – Sampling (Summary)

Sampling – process of selecting the sample of individuals who will participate (be observed or

questioned).

Samples and Populations

• A sample – the group on which information is obtained.
  
• Population – the larger group to which one hopes to apply the results.
  

In educational research – population is usually a group of persons (students, teachers, or other individuals) who possess certain characteristics. Or group of classrooms, schools,or facilities.

Random Sampling methods include:

• Simple random sampling – choosing elementary units in search a way that each unit in the population has an equal chance of being selected. A simple random sample is free from sampling bias. For example, there are 100 students in your class. You want a sample of 20 from these 100 and you have their names listed on a piece of paper may be in an alphabetical order. If you choose to use systematic random sampling, divide 100 by 20, you will get 5. Randomly select any number between 1 and five. Suppose the number you have picked is 4, that will be your starting number. So student number 4 has been selected. From there you will select every 5th name until you reach the last one, number one hundred. You will end up with 20 selected students.
  
• Stratified random sampling - sample is obtained by independently selecting a separate simple random sample from each population stratum. A population can be divided into different groups may be based on some characteristic or variable like income of education. Like any body with ten years of education will be in group A, between 10 and 20 group B and between 20 and 30 group C. These groups are referred to as strata. You can then randomly select from each stratum a given number of units which may be based on proportion like if group A has 100 persons while group B has 50, and C has 30 you may decide you will take 10% of each. So you end up with 10 from group A, 5 from group B and 3 from group C.
  
• Cluster random sampling - sample is obtained by selecting clusters from the population on the basis of simple random sampling. The sample comprises a census of each random cluster selected. For example, a cluster may be some thing like a village or a school, a state. So you decide all the elementary schools in Newyork State are clusters. You want 20 schools selected. You can use simple or systematic random sampling to select the schools, then every school selected becomes a cluster.
  
• Two-stage random sampling – selects groups randomly and then chooses individuals randomly from these groups
  

Nonrandom sampling methods include:

• Systematic sampling - A systematic random sample is obtained by selecting one unit on a random basis and choosing additional elementary units at evenly spaced intervals until the desired number of units is obtained. For example, there are 100 students in your class. You want a sample of 20 from these 100 and you have their names listed on a piece of paper may be in an alphabetical order. If you choose to use systematic random sampling, divide 100 by 20, you will get 5. Randomly select any number between 1 and five. Suppose the number you have picked is 4, that will be your starting number. So student number 4 has been selected. From there you will select every 5th name until you reach the last one, number one hundred. You will end up with 20 selected students.
  
• Convenience sampling - A convenience sample results when the more convenient elementary units are chosen from a population for observation.
  
• Purposive sampling - selects information rich cases for in depth study. Size and specific cases depend on the study purpose.
  

Sample Size

sample size depends on the nature of the analysis to be performed, the desired precision of the estimates one wishes to achieve, the kind and number of comparisons that will be made, the number of variables that have to be examined simultaneously and how heterogenous a universe is sampled. For example, if the key analysis of a randomized experiment consists of computing averages for experimentals and controls in a project and comparing differences, then a sample under 100 might be adequate, assuming that other statistical assumptions hold.

Sample size can be determined by various constraints. For example, the available funding may prespecify the sample size. When research costs are fixed, a useful rule of thumb is to spent about one half of the total amount for data collection and the other half for data analysis. This constraint influences the sample size as well as sample design and data collection procedures.

Conclusion

In conclusion, it can be said that using a sample in research saves mainly on money and time, if a suitable sampling strategy is used, appropriate sample size selected and necessary precautions taken to reduce on sampling and measurement errors, then a sample should yield valid and reliable information. Details on sampling can be obtained from the references included below and many other books on statistics or qualitative research which can be found in libraries.

References

1. Text book
   
2. Sampling In Research Mugo Fridah W.
   

   http://www.socialresearchmethods.net/tutorial/Mugo/tutorial.htm